Apache has developed a clear AI roadmap focused on delivering measurable business value. By prioritizing high-impact projects and applying a structured framework that defines success criteria from the outset, Apache ensures its AI initiatives are scalable and adaptable to rapid technological advancements.
In this session, Reza will present three high-ROI use cases that illustrate this approach:
- Remote Operations Agentic Summarization:
Sythensising key events, alarms and notifications from ROC’s
Results: Time savings and an incident response time of 10s%
Lessons Learnt: Clarity and context in summaries vital for decision effectiveness
- Power & Energy Demand Modeling and Optimization:
Informing asset & equipment decisions based on power demand
Results: Energy cost reduction
Lessons Learnt: The importance of the granularity of data and how predictive accuracy boosts efficiency
- Water Takeaway Modeling & Decision Support:
Implementing water cut and WOR ‘creaming curves’ to determine how to best route and prioritize production in water-constrained environments
Results: Penalty reductions and operational efficiency
Lessons Learnt: Why data accuracy is critical and how real-time updates enhance forecasting reliability